Lead Data Scientist - Banking (Cornet)
hace 17 horas
Pineda de Mar
ph3Overview /h3pOur Technology team drives the evolution of our Technology, Engineering, Data, Product and User Experience functions. With a keen focus on delivering cutting‑edge solutions, we shape the digital landscape for our customers, readers and users. From revolutionizing visuals to optimizing tools and harnessing the power of data, mobile, video and social platforms, our team is committed to providing a seamless and immersive experience across all touchpoints. /ppCollaborating closely with our newsrooms and strategic partners, we spearhead the development of groundbreaking products and technologies. Dow Jones is seeking a Lead Data Scientist to own and advance the architecture and delivery of AI‑powered Search and discovery platforms across our products. As part of the GenAI, Search, and Personalization organization, this role will specifically lead Search data science while collaborating closely with peer leads across Generative AI and Personalization. /ph3Responsibilities /h3pYou will define and execute the technical strategy for scalable, production‑grade search systems, building and optimizing machine learning and information retrieval pipelines that power relevance, ranking, and content discovery. This role emphasizes applied, engineering‑focused data science, partnering closely with engineering teams to design reliable, high‑performance search infrastructure and deploy modern capabilities such as semantic retrieval, hybrid and vector search, retrieval‑augmented generation (RAG), and LLM‑powered conversational discovery experiences. Own the end‑to‑end delivery of search and discovery data science initiatives, from problem framing and experimentation through production deployment and performance monitoring. /ppEstablish and evolve relevance and evaluation frameworks, defining success metrics and driving continuous improvement in search quality, engagement, and business impact. Work alongside peer leads across Generative AI and Personalization to deliver cohesive and consistent user discovery strategies. /ppProvide technical leadership and mentorship to data scientists, setting high standards for experimentation, model development, and production readiness. /ph3Qualifications /h3ulliD. in Computer Science, Information Retrieval, Machine Learning, Data Science, or a related quantitative field (or equivalent practical experience). /lili4 – 7 years of industry experience in applied machine learning, search, or information retrieval, including experience leading complex, cross‑functional initiatives. /liliHands‑on experience building and deploying semantic, vector, and hybrid search solutions, including familiarity with embedding models and retrieval‑augmented generation (RAG) patterns. /liliDeep experience applying machine learning and/or LLM‑based techniques to real‑world discovery, recommendation, or knowledge retrieval problems. /liliAdvanced programming skills in Python and strong experience with ML and LLM ecosystems (e.g., PyTorch, Hugging Face, retrieval and evaluation tooling, or similar frameworks). /liliExperience designing experimentation and evaluation frameworks for search quality, including offline relevance metrics and online testing methodologies. /liliProven experience deploying production ML systems using cloud infrastructure (e.g., AWS, GCP, or similar), including performance optimization and scalability considerations. /liliFamiliarity with distributed systems, data pipelines, and production deployment practices, including containerization and orchestration technologies. /liliDemonstrated leadership and mentorship experience, with a track record of elevating technical standards and supporting team growth. /li /ul /p #J-18808-Ljbffr
